Survival costs of reproduction vary with age in North American red squirrels
Bibliographic record
Abstract
The costs of reproduction are expected to be higher under unfavourable conditions, so that breeding in years of low food supply should have important costs. In addition, the costs of reproduction may be contingent on the age of individuals, and young growing and old senescent individuals should suffer higher costs than the prime-age ones. We tested these predictions by investigating the costs of reproduction as a function of food availability and age in female North American red squirrels using the long-term data on survival and reproduction. We found that the costs of reproduction were independent of food supply, and we did not detect any trade-off between the current and future reproduction. We also did not detect any survival cost of reproduction for the prime-age females, but found evidence for survival costs in yearlings and old (6 years or above) females with successfully breeding individuals having a lower chance of survival compared with unsuccessful or non-breeding ones. These results supported our prediction that the costs of reproduction depended on the age of female red squirrels and were higher in young growing and old senescent individuals. Our study also indicated that, in contrast to large herbivores, heterogeneity in individual quality and viability selection in red squirrels do not affect the study of trade-offs and of the age variation in life-history traits.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".